import tensorflow as tf
import numpy as np
from matplotlib import pyplot as plt


def himmelblau(x):
    return (x[0] ** 2 + x[1] - 11) ** 2 + (x[0] + x[1] ** 2 - 7) ** 2


x = np.arange(-6,6,0.1)
y = np.arange(-6,6,0.1)
print('x,y shape:',x.shape,y.shape)
X,Y = np.meshgrid(x,y)
print('X,Y maps:',X.shape,Y.shape )
Z = himmelblau([X,Y])

fig = plt.figure('himmelblau')
ax = fig.gca(projection='3d')
ax.plot_surface(X,Y,Z)
ax.view_init(60,-30)
ax.set_xlabel('x')
ax.set_ylabel('y')
plt.show()

x = tf.constant([-4.,0.])

for step in range(200):

    with tf.GradientTape() as tape:
        tape.watch([x])
        y = himmelblau(x)
    grads = tape.gradient(y,[x])[0]
    x -= 0.01*grads

    if step % 20 == 0:
        print('step {}:x = {}, f(x) = {}'.format(step,x.numpy(),y.numpy()))

